scholarly journals An Ontology-Based Model for Treatment Guidelines of Internet and Games Addiction

2019 ◽  
Vol 8 (2S2) ◽  
pp. 113-117
Keyword(s):  
Risk Factors ◽  
Recommendation System ◽  
Treatment Guidelines ◽  
Difficult Problem ◽  
Ontology Development ◽  
The Internet ◽  
Evaluation Result ◽  
Domain Experts ◽  
States Data ◽  
Profile Characteristics

Internet and games addiction will become a difficult problem for the parents, because the internet and games easier to access and has more contents. Thus, the number of internet and games addiction will be increasing in the future. This study recommends ontology expansion for treatment guidelines of internet and games addiction that will use as the component of recommendation system in web technology. This study’s methodology can be condensed into three states; data collection ontology development, and evaluation. This ontology included seven main classes, there are profile, characteristics, risk factors, devices, treatment, and GAST. The evaluation result that conducted by domain experts included a highly-superior concentration of 88.34%, which confirms that this ontology may be employed for developing a recommendation system.

scholarly journals Evaluating the Bovine Tuberculosis Eradication Mechanism and Its Risk Factors in England’s Cattle Farms

2021 ◽  
Vol 18 (7) ◽  
pp. 3451
Author(s):  
Tabassom Sedighi ◽  
Liz Varga
Keyword(s):  
Risk Factors ◽  
Bovine Tuberculosis ◽  
Animal Health ◽  
Dynamic Bayesian Network ◽  
Policy Makers ◽  
Domain Experts ◽  
Actual Experience ◽  
Complex Evaluation ◽  
Risk Areas ◽  
Cattle Farms

Controlling bovine tuberculosis (bTB) disease in cattle farms in England is seen as a challenge for farmers, animal health, environment and policy-makers. The difficulty in diagnosis and controlling bTB comes from a variety of factors: the lack of an accurate diagnostic test which is higher in specificity than the currently available skin test; isolation periods for purchased cattle; and the density of active badgers, especially in high-risk areas. In this paper, to enable the complex evaluation of bTB disease, a dynamic Bayesian network (DBN) is designed with the help of domain experts and available historical data. A significant advantage of this approach is that it represents bTB as a dynamic process that evolves periodically, capturing the actual experience of testing and infection over time. Moreover, the model demonstrates the influence of particular risk factors upon the risk of bTB breakdown in cattle farms.

Abstract 57: Risk Factors For Severe Reductions In Blood Pressure After Treatment Of Severe Inpatient Hypertension

Hypertension ◽  
2021 ◽  
Vol 78 (Suppl_1) ◽  
Author(s):  
Lama Ghazi ◽  
Fan Li ◽  
Eric Chen ◽  
Michael Simonov ◽  
Yu Yamamoto ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Cohort Study ◽  
Hospital Admission ◽  
Antihypertensive Treatment ◽  
Treatment Guidelines ◽  
P Value ◽  
Antihypertensive Medications ◽  
Black Race ◽  
Oral Medications

Background: Incident severe HTN during hospitalization is far more common than admission for HTN, however treatment guidelines are lacking. Severe inpatient HTN is poorly studied, therefore our goal is to characterize inpatients who develop severe HTN and assess BP response to antihypertensive treatment. Methods: This is a cohort study of adults admitted for reasons other than HTN and developed severe HTN within a single healthcare system. We defined severe inpatient HTN as the first documentation of BP elevation (>180 systolic or >110 diastolic) at least 1 hour after hospital admission. Treatment was defined as receiving antihypertensive medications within 6 hours of BP elevation. We studied the association between treatment and BP drop ≥30%. Results: Among 224,265 hospitalized adults, 23,147 developed severe HTN of which 40% were treated. Compared to inpatients who did not develop severe HTN, those who did were older, more commonly women and Black, and had more comorbidities. Of the treated and untreated patients, 45.5 and 46.4% had a MAP drop ≥30% (p-value= 0.2). Risk factors for severe MAP drop include older age, Black race, HTN, and diabetes. Additionally, treatment vs. no treatment and treatment with intravenous vs. oral medications were associated with greater odds of MAP drop ≥30% ( Table 1 ). Conclusion: While there was no difference in the proportion of treated and untreated patients with severe MAP reduction, after adjustment for factors independently associated with HTN we found that treatment was associated with severe BP drop. Further research is needed to phenotype inpatients with severe HTN to help establish treatment guidelines.

scholarly journals Movie Recommenadation System

2021 ◽  
Vol 9 (4) ◽  
pp. 13-16
Author(s):  
Gandhali Malve ◽  
Lajree Lohar ◽  
Tanay Malviya ◽  
Shirish Sabnis
Keyword(s):  
Machine Learning ◽  
Recommender System ◽  
Recommendation System ◽  
Learning Algorithms ◽  
Recommendation Systems ◽  
Machine Learning Algorithms ◽  
The Internet ◽  
Amount Of Information ◽  
System Recommendation ◽  
User Ratings

Today the amount of information in the internet growth very rapidly and people need some instruments to find and access appropriate information. One of such tools is called recommendation system. Recommendation systems help to navigate quickly and receive necessary information. Many of us find it difficult to decide which movie to watch and so we decided to make a recommender system for us to better judge which movie we are more likely to love. In this project we are going to use Machine Learning Algorithms to recommend movies to users based on genres and user ratings. Recommendation system attempt to predict the preference or rating that a user would give to an item.

The Harvey Project

2011 ◽  
pp. 185-194 ◽  
Author(s):  
Robert S. Stephenson
Keyword(s):  
Learning Objects ◽  
Task Demands ◽  
The Internet ◽  
Instructional Designers ◽  
Domain Experts ◽  
Content Development ◽  
On Line ◽  
Use Of The Internet ◽  
Rich Content ◽  
The Web

The rise of the Internet has started a knowledge revolution whose extent can only be guessed at. The last revolution of this magnitude, brought on by the printing press, led to the proliferation of books and the rise of the modern university system. If universities are to survive the latest knowledge revolution, they must adapt with unaccustomed speed and learn how to use the Internet for more effective teaching. Most universities adopt a limited approach to building on-line courses. However, many studies have found that merely transplanting materials to the Web does not significantly improve learning (Russell, 1999). In fact, handouts, slides, and viewgraphs that have been “repurposed” for the Web are sometimes derisively referred to as “shovelware” (Fraser, 1999). So while moving existing materials to the Web may increase their accessibility, it will not necessarily improve their effectiveness. The Internet’s real value as a medium and teaching platform is that it makes possible rich, interactive content such as simulations, animations, and 3-D models. These learning objects, or rich content, can significantly enhance learning, especially in the sciences, and can be just as useful inside the classroom as outside. The difficulty is how to create this enhanced content, since the task demands a broad range of technical skills and enormous effort. Besides faculty domain experts and experienced teachers, rich content development typically requires illustrators, Web designers, programmers, instructional designers, testers, and Webmasters. The only way faculty and institutions can meet this challenge is to embrace collaboration more broadly and seriously than they have in the past. One approach is the multi-institutional consortium. Another solution is a collaboration of faculty to build rich content in their discipline. This chapter chronicles an example of the latter sort: a bottom-up, cross-institutional project. For such a grass roots collaboration to succeed, it must recruit many faculty pioneering the use of the Internet in their teaching, as well as artists and technical professionals. It must offer collaborators an incentive to participate, and it must attract not only volunteers, but also institutional and agency funding as well. Finally, as a pioneering project, it must create standards and develop paradigms as it goes. This case study describes a work-in-progress to solve these issues.

Reconstructing Diffusion Model for Virality Detection in News Spread Networks

2021 ◽  
pp. 98-111
Author(s):  
Kritika Jain ◽  
Ankit Garg ◽  
Somya Jain
Keyword(s):  
Diffusion Model ◽  
Experimental Analysis ◽  
Recommendation System ◽  
Continuous Process ◽  
The Internet ◽  
Temporal Network ◽  
Temporal Networks ◽  
Spreading Pattern ◽  
Effective Product ◽  
Business Technology

In today's competitive world, organizations take advantage of widely-available data to promote their products and increase their revenue. This is achieved by identifying the reader's preference for news genre and patterns in news spread network. Spreading news over the internet seems to be a continuous process which eventually triggers the evolution of temporal networks. This temporal network comprises of nodes and edges, where node corresponds to published articles and similar articles are connected via edges. The main focus of this article is to reconstruct a susceptible-infected (SI) diffusion model to discover the spreading pattern of news articles for virality detection. For experimental analysis, a dataset of news articles from four domains (business, technology, entertainment, and health) is considered and the articles' rate of diffusion is inferred and compared. This will help to build a recommendation system, i.e. recommending a particular domain for advertisement and marketing. Hence, it will assist to build strategies for effective product endorsement for sustainable profitability.

Incidental finding of type A aortic dissection in a paediatric heart transplant recipient

2019 ◽  
Vol 29 (09) ◽  
pp. 1219-1221
Author(s):  
Laura D’Addese ◽  
Rukmini Komarlu ◽  
Kenneth Zahka
Keyword(s):  
Risk Factors ◽  
Aortic Dissection ◽  
Heart Transplantation ◽  
Treatment Guidelines ◽  
Incidental Finding ◽  
Heart Transplant Recipient ◽  
Orthotopic Heart Transplantation ◽  
Aortic Dilatation ◽  
Size Mismatch ◽  
Type A Aortic Dissection

AbstractAortic dissection causes significant morbidity and mortality in adults and treatment guidelines are based on well-documented risk factors. Conversely, dissection after orthotopic heart transplantation is very rare, especially in the absence of infection, hypertension, or donor–recipient aortic size mismatch. Several forms of CHD are associated with aortic dilatation, but the incidence of aortic dissection and aneurysm in children is also low, which makes use of adult guidelines in children challenging. We present a 17-year-old Amish female with a homozygous gene mutation in the MYBPC3 gene known to cause lethal, infantile hypertrophic cardiomyopathy. She underwent orthotopic heart transplantation and then developed an asymptomatic aortic dissection despite no known risk factors.

scholarly journals Internet Access and Breast Cancer Awareness Among Akure Residents

2018 ◽  
Vol 4 (Supplement 3) ◽  
pp. 4s-4s
Author(s):  
Betty Anyanwu-Akeredolu
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Internet Access ◽  
The Internet ◽  
Cancer Knowledge ◽  
Cancer Awareness ◽  
Breast Self Examination ◽  
Breast Cancer Awareness ◽  
Breast Cancer Knowledge ◽  
Self Examination

Purpose Of the leading types of cancer in women, breast cancer presents with the highest number of cases and is the leading cause of cancer death in less developed countries. Despite the promising positive impact of the Internet on breast cancer awareness, there is a paucity of information on the effect of Internet access on breast cancer knowledge in Nigeria. Therefore, the aim of this study was to determine the effect of Internet access on breast cancer knowledge and the perceived benefit of breast self-examination among adults residing in Akure Town, Ondo State, Nigeria. Methods A descriptive cross-sectional study design was used to determine the effect of access to the Internet on breast cancer knowledge and the perceived benefit of breast self-examination among Akure residents. The study was conducted in 295 men and women age 18 to 60 years residing in Akure who were selected using a systematic sampling technique. A telephone survey was used to collect data. Simple frequency distribution was used to describe the data, and bivariable logistic regression was used to test the association between variables. Results Almost all adults residing in Akure are aware of breast cancer and more than one half have a good knowledge of the disease. Although more than one half of the study population was found to have a good knowledge of breast cancer, most adults do not have knowledge of the risk factors of breast cancer. Nearly 97% of the 84% of participants who have ever conducted breast self-examination does so at least once in a month. Adults residing in Akure who have access to the Internet were more than two times more likely to have a good knowledge of breast cancer compared with their counterparts with no Internet access. Conclusion Knowledge of breast cancer is above average among Akure adults; however, more than one half of the adult populace in Akure still lacks adequate knowledge of the risk factors of breast cancer. Breast cancer awareness programs that are targeted at Akure residents should emphasize breast cancer risk factors and use the platform provided by the Internet. AUTHOR’S DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/site/ifc . No COIs from the author.

Using the Internet for Knowledge Acquisition in Expert Systems Development: A Case Study

1996 ◽  
Vol 11 (3) ◽  
pp. 223-234
Author(s):  
Kathleen K. Molnar ◽  
Ramesh Sharda
Keyword(s):  
Expert System ◽  
Knowledge Acquisition ◽  
Electronic Mail ◽  
System Development ◽  
Cost Savings ◽  
Lessons Learned ◽  
The Internet ◽  
Domain Experts ◽  
Use Of The Internet ◽  
Multiple Experts

Knowledge acquisition is a major task in expert system development. This paper proposes one way of acquiring knowledge for expert system development: through the use of the Internet. Internet resources (e.g. Usenet groups, ListServ discussion lists, archive sites and on-line literature/database searches) are knowledge sources. Internet tools such as newsreaders, electronic mail, Telnet, FTP, gophers, archie, WAIS and World Wide Web provide access to these sources. The results of an exploratory study that examined the use of the Internet as a knowledge source are presented here in conjunction with a framework for using the Internet in the planning phase. Four major advantages can be found in this: the availability of multiple experts in multiple domains, the interaction of domain experts and end users, time/cost savings, and convenience. The lessons learned and some additional issues are also presented.

scholarly journals Prevalence of daytime sleeping in the working population from estimates of nocturnal work shift

2015 ◽  
Vol 1 (1) ◽  
pp. 44
Author(s):  
Carlos Siordia ◽  
Athena K Ramos
Keyword(s):  
Risk Factors ◽  
Labor Force ◽  
Community Dwelling ◽  
Minority Status ◽  
Working Population ◽  
Cross Sectional ◽  
States Data ◽  
Low Levels ◽  
Nationally Representative ◽  
Estimate Prevalence

Background: Sunlight has been linked the circadian rhythms that regulate sleep. Few studies have attempted to provide estimates on the size of the “daytime sleeper” population. Specific aims: Estimate prevalence of daytime sleepers in the labor force population and identify which demographic characteristics are risk factors for daytime sleeping.Methods: Cross-sectional, community-dwelling, nationally representative, observational study used information on 6,405,063 labor force participants representing 132,682,344 individuals in the contiguous United States. Data from the American CommunitySurvey (ACS), Public Use Microdata Sample (PUMS), 2009-2013 (5-year) file was used to identify daytime sleepers (i.e., those who arrived at work between 7:00 PM and 2:59 AM).Findings: While nighttime sleepers represented 65.9% (n = 87,426,814) of those in the labor force population, daytime sleepers represent 3.3% (n = 4,344,311). Race-ethnic minority status, being disabled, and having low levels of educational attainment were found to be risk factors for daytime sleeping.Conclusions: Even though relatively small, the objectively large (4.3 million) number of daytime sleepers requires sleepresearch to invest resources in understanding how health varies in this population relative to those who primarily sleep in theabsence of sunlight.

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